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Title: The effect of interfirm financial transactions on the credit risk of small and medium-sized enterprises
Authors: Vinciotti, V
Tosetti, E
Moscone, F
Lycett, M
Keywords: credit risk modelling;financial transactions;small and medium-sized enterprises
Issue Date: 2019
Publisher: John Wiley & Sons Ltd on behalf of the Royal Statistical Society
Citation: Journal of the Royal Statistical Society. Series A: Statistics in Society, 2019, 182(4): 1205 - 1226
Abstract: © 2019 The Authors. Despite the recognized importance of interfirm financial links in determining a company's performance, only a few studies have incorporated proxies for interfirm links in credit risk models, and none of these use real financial transactions. We estimate a credit risk model for small and medium-sized enterprises, augmented with information on observed interfirm financial transactions. We exploit a novel data set on about 60000 companies based in the UK and their financial transactions over the years 2015 and 2016. We develop several network-augmented credit risk models and compare their prediction performance with that of a conventional credit risk model that includes only a set of financial ratios. We find that augmenting a default risk model with information on the transaction network makes a significant contribution to increasing the default prediction power of risk models built specifically for small and medium-sized enterprises. Our results may help bankers and credit scoring agencies to improve the credit scoring of these companies, ultimately reducing their propensity to apply excessive lending restrictions.
ISSN: 0964-1998
Appears in Collections:Dept of Mathematics Research Papers

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